Sunday, 17 June 2018

Data sharing in PLOS ONE: An analysis of Data Availability Statements

By Lisa M. Federer et al.

Published 2 May 2018

https://doi.org/10.1371/journal.pone.0194768
Abstract

A number of publishers and funders, including PLOS, have recently adopted policies requiring researchers to share the data underlying their results and publications. Such policies help increase the reproducibility of the published literature, as well as make a larger body of data available for reuse and re-analysis. In this study, we evaluate the extent to which authors have complied with this policy by analyzing Data Availability Statements from 47,593 papers published in PLOS ONE between March 2014 (when the policy went into effect) and May 2016. Our analysis shows that compliance with the policy has increased, with a significant decline over time in papers that did not include a Data Availability Statement. However, only about 20% of statements indicate that data are deposited in a repository, which the PLOS policy states is the preferred method. More commonly, authors state that their data are in the paper itself or in the supplemental information, though it is unclear whether these data meet the level of sharing required in the PLOS policy. These findings suggest that additional review of Data Availability Statements or more stringent policies may be needed to increase data sharing.

Thursday, 14 June 2018

It’s Time to Make Your Data Count!

From : https://makedatacount.org/2018/06/05/its-time-to-make-your-data-count/

One year into our Sloan funded Make Data Count project, we are proud to release Version 1 of standardized data usage and citation metrics!
As a community that values research data it is important for us to have a standard and fair way to compare metrics for data sharing. We know of and are involved in a variety of initiatives around data citation infrastructure and best practices; including Scholix, Crossref and DataCite Event Data. But, data usage metrics are tricky and before now there had not been a group focused on processes for evaluating and standardizing data usage. Last June, members from the MDC team and COUNTERbegan talking through what a recommended standard could look like for research data.

Mapping the PID Landscape

This post was co-authored with Christoper Brown and Neil Jacobs (Jisc), Josh Brown and Laure Haak(ORCID), and Clifford Tatum (SURF)
The landscape of research information is largely closed to us. We rely on original research to solve many of the challenges facing humanity, to improve lives, and to advance human understanding, and we invest in it accordingly. However, when we survey the map of our research world it is filled with gaps. We pass along a few well-trodden roads (too often paying a substantial toll for the privilege) and we can only wonder about what lies just over the horizon.
We can point to many contributing factors: business models that militate against the sharing of information; aggregation of research analytics for local strategic purposes; technological barriers to linking information between sources; cultural practices that reward and privilege a small slice of research activity; and systems that emphasise hard sciences and anglophone literature. Any and all of these can, and do, hide some of the richness of research endeavour. However, these systemic challenges are not the focus of this discussion. Instead, our focus is on the gaps in our understanding of the landscape: the empty parts of the research map.
https://orcid.org/blog/2018/06/07/mapping-pid-landscape

Thursday, 7 June 2018

Ten reasons to share your data

Making data available to the larger scientific community has many benefits.
27 April 2018